Quantitative diffusion measurements using the open-source software PyFRAP

Alexander Bläßle, Gary Soh, Theresa Braun, David Mörsdorf, Hannes Preiß, Ben M. Jordan and Patrick Müller ()
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Alexander Bläßle: Friedrich Miescher Laboratory of the Max Planck Society
Gary Soh: Friedrich Miescher Laboratory of the Max Planck Society
Theresa Braun: Friedrich Miescher Laboratory of the Max Planck Society
David Mörsdorf: Friedrich Miescher Laboratory of the Max Planck Society
Hannes Preiß: Friedrich Miescher Laboratory of the Max Planck Society
Ben M. Jordan: Harvard University
Patrick Müller: Friedrich Miescher Laboratory of the Max Planck Society

Nature Communications, 2018, vol. 9, issue 1, 1-14

Abstract: Abstract Fluorescence Recovery After Photobleaching (FRAP) and inverse FRAP (iFRAP) assays can be used to assess the mobility of fluorescent molecules. These assays measure diffusion by monitoring the return of fluorescence in bleached regions (FRAP), or the dissipation of fluorescence from photoconverted regions (iFRAP). However, current FRAP/iFRAP analysis methods suffer from simplified assumptions about sample geometry, bleaching/photoconversion inhomogeneities, and the underlying reaction-diffusion kinetics. To address these shortcomings, we developed the software PyFRAP, which fits numerical simulations of three-dimensional models to FRAP/iFRAP data and accounts for bleaching/photoconversion inhomogeneities. Using PyFRAP we determined the diffusivities of fluorescent molecules spanning two orders of magnitude in molecular weight. We measured the tortuous effects that cell-like obstacles exert on effective diffusivity and show that reaction kinetics can be accounted for by model selection. These applications demonstrate the utility of PyFRAP, which can be widely adapted as a new extensible standard for FRAP analysis.

Date: 2018
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DOI: 10.1038/s41467-018-03975-6

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